Addressing Beacon Re-Identification Attacks: Quantification and Mitigation of Privacy Risks

The Global Alliance for Genomics and Health (GA4GH) created the Beacon Project as a means of testing the willingness of data holders to share genetic data in the simplest technical context query for the presence of a specified nucleotide at a given position within a chromosome. Each participating site (or “beacon”) is responsible for assuring that genomic data are exposed through the Beacon service only with the permission of the individual to whom the data pertains, and in accordance with the GA4GH policy and standards. While recognizing the inference risks associated with large-scale data aggregation, and the fact that some beacons contain sensitive phenotypic associations that increase privacy risk, the GA4GH adjudged the risk of re-identification based on the binary yes/no allele-presence query responses as acceptable. However, recent work demonstrated that, given a beacon with specific characteristics (including relatively small sample size, and an adversary who possesses an individual’s whole genome sequence), the individual’s membership in a beacon can be inferred through repeated queries for variants present in the individual’s genome. In this paper, we propose three practical strategies for reducing re-identification risks in beacons. The first two strategies manipulate the beacon such that the presence of rare alleles is obscured; the third strategy budgets the number of accesses per user for each individual genome. Using a beacon containing data from the 1000 Genomes Project, we demonstrate that the proposed strategies can effectively reduce re-identification risk in beacon-like datasets

Identification of floR Variants Associated With a Novel Tn4371-Like Integrative and Conjugative Element in Clinical Pseudomonas aeruginosa Isolates

Florfenicol is widely used to control respiratory diseases and intestinal infections in food animals. However, there are increasing reports about florfenicol resistance of various clinical pathogens. floR is a key resistance gene that mediates resistance to florfenicol and could spread among different bacteria. Here, we investigated the prevalence of floR in 430 Pseudomonas aeruginosa isolates from human clinical samples and identified three types of floR genes (designated floR, floR-T1 and floR-T2) in these isolates, with floR-T1 the most prevalent (5.3%, 23/430). FloR-T2 was a novel floR variant identified in this study, and exhibited less identity with other FloR proteins than FloRv. Moreover, floR-T1 and floR-T2 identified in P. aeruginosa strain TL1285 were functionally active and located on multi-drug resistance region of a novel incomplete Tn4371-like integrative and conjugative elements (ICE) in the chromosome. The expression of the two floR variants could be induced by florfenicol or chloramphenicol. These results indicated that the two floR variants played an essential role in the host’s resistance to amphenicol and the spreading of these floR variants might be related with the Tn4371 family ICE

Ultrathin, Graphene‐in‐Polyimide Strain Sensor via Laser‐Induced Interfacial Ablation of Polyimide

Abstract Laser‐induced graphene sensors have attracted considerable interest in various fields; however, the low sensitivity and conformability limit their further applications in measuring soft, large deformable structures. Here, an innovative method of interface ablation is presented to convert the interfacial polyimide into graphene by nanosecond ultraviolet laser (308 nm). Significantly different from the traditional laser surface ablation, interface ablation demonstrates its unique capacity to produce high‐quality graphene with limited ablation depth, which benefits from the combined effect of highly concentrated temperature distribution, the confinement of reaction product, and a unique ablation mode dominated by heat conduction. Using this method, an ultrathin (8 µm), graphene‐in‐polyimide (GiP) strain sensor is obtained, which is six times thinner than that prepared by the traditional surface ablation. The ultrathin GiP sensors exhibit excellent conformability (small bending radius of 400 µm), high strain sensitivity (24.8), and high force sensitivity (4.2 N−1). Demonstrations of this GiP strain sensor in the deformation measurement of the morphing aircraft (e.g., bending, twisting, and impact) illustrate its powerful abilities in the health monitoring of equipment, thus providing engineering opportunities for smart devices requiring accurate deformation measurement

Addressing Beacon re-identification attacks: quantification and mitigation of privacy risks.

The Global Alliance for Genomics and Health (GA4GH) created the Beacon Project as a means of testing the willingness of data holders to share genetic data in the simplest technical context-a query for the presence of a specified nucleotide at a given position within a chromosome. Each participating site (or "beacon") is responsible for assuring that genomic data are exposed through the Beacon service only with the permission of the individual to whom the data pertains and in accordance with the GA4GH policy and standards.While recognizing the inference risks associated with large-scale data aggregation, and the fact that some beacons contain sensitive phenotypic associations that increase privacy risk, the GA4GH adjudged the risk of re-identification based on the binary yes/no allele-presence query responses as acceptable. However, recent work demonstrated that, given a beacon with specific characteristics (including relatively small sample size and an adversary who possesses an individual's whole genome sequence), the individual's membership in a beacon can be inferred through repeated queries for variants present in the individual's genome.In this paper, we propose three practical strategies for reducing re-identification risks in beacons. The first two strategies manipulate the beacon such that the presence of rare alleles is obscured; the third strategy budgets the number of accesses per user for each individual genome. Using a beacon containing data from the 1000 Genomes Project, we demonstrate that the proposed strategies can effectively reduce re-identification risk in beacon-like datasets

Addressing Beacon re-identification attacks: quantification and mitigation of privacy risks

The Global Alliance for Genomics and Health (GA4GH) created the Beacon Project as a means of testing the willingness of data holders to share genetic data in the simplest technical context—a query for the presence of a specified nucleotide at a given position within a chromosome. Each participating site (or "beacon”) is responsible for assuring that genomic data are exposed through the Beacon service only with the permission of the individual to whom the data pertains and in accordance with the GA4GH policy and standards. While recognizing the inference risks associated with large-scale data aggregation, and the fact that some beacons contain sensitive phenotypic associations that increase privacy risk, the GA4GH adjudged the risk of re-identification based on the binary yes/no allele-presence query responses as acceptable. However, recent work demonstrated that, given a beacon with specific characteristics (including relatively small sample size and an adversary who possesses an individual's whole genome sequence), the individual's membership in a beacon can be inferred through repeated queries for variants present in the individual's genome. In this paper, we propose three practical strategies for reducing re-identification risks in beacons. The first two strategies manipulate the beacon such that the presence of rare alleles is obscured; the third strategy budgets the number of accesses per user for each individual genome. Using a beacon containing data from the 1000 Genomes Project, we demonstrate that the proposed strategies can effectively reduce re-identification risk in beacon-like datasets